JASA Highlights
What Is the JASA Reviews?
David Banks, Walter W. Piegorsch, Stephen L. Portnoy, and Dalene K. Stangl
W
hen statisticians think
of review papers, they
Books Reviewed
often think of the jour-
nal Statistical Science, but JASA
Applied Stochastic Processes
also prints review papers and
Mario Lefebvre
would like to print more of them.
What type of review paper is suit-
Bayesian Statistics 8
able for JASA? The following list
J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman,
of criteria is from a review sub-
A. F. M. Smith, and M. West (eds.)
mitted several years ago. Because
reviews are confidential, we
Benchmarking, Temporal Distribution, and Reconciliation
cannot release the name of the
Methods for Time Series
author, but thanks are in order
Estela Bee Dagum and Pierre A. Cholette
as the author succinctly
describes the expectations for
Contemporary Bayesian and Frequentist Statistical Research
JASA review papers.
Methods for Natural Resource Scientists
A JASA review article must
Howard B. Stauffer
accomplish three or more of the following goals:
Consolidate theory and methods that are scattered in the
Correlated Data Analysis: Modeling, Analytics,
literature
and Applications
Peter X.-K. Song
Provide new insights into the problem
Demonstrate key aspects of the methods using simple or
Data Clustering: Theory, Algorithms, and Applications
Guojun Gan, Chaoqun Ma, and Jianhong Wu
unified methods
Identify challenging features and formulate them in a
Design and Modeling for Computer Experiments
fashion that facilitates future research
Kai-Tai Fang, Runze Li, and Agus Sudjianto
Review papers leave the reader with deeper insight into the
Elementary Bayesian Biostatistics
issues associated with the topic. Because some novelty (either in
Lemuel A. Moyé
insight into the problem or in unification of methods) is required,
it is challenging to write a high-quality review paper of this caliber,
Hidden Markov Models in Finance
but we would love to see more submissions.
Rogemar S. Mamon and Robert J. Elliott (eds.)
A second component of JASA Reviews is the book reviews.
About 300 books are submitted for review by publishers each year.
Linear Model Theory: Univariate, Multivariate, and
Reviews of about 100 of these books appear in JASA. Book reviews
Mixed Models
aim to let readers know the content, intended audience, and qual-
Keith E. Muller and Paul W. Stewart
ity of these books. Book reviews are comparative and evaluative,
answering several key questions. What topic does the book cover?
Linking and Aligning Scores and Scales
How does the book compare to other books on the same topic?
Neil J. Dorans, Mary Pommerich, and Paul W. Holland (eds.)
Does the book fill a new niche? Is the book accurate? Is it read-
able? Who is the audience? What level of background in statistics
Long-Memory Time Series: Theory and Methods
is needed to read the book? Does the book meet the needs of its
Wilfredo Palma
intended readership?
If you have a review paper, or if you know of a book that has
Matrix Algebra: Theory, Computations, and Applications
been missed, do let us know.
in Statistics
Theory and Methods
James E. Gentle
The Theory and Methods section highlights recent research in func-
Missing Data in Clinical Studies
tional or “repeated measures” data. Three of the first four papers
Geert Molenberghs and Michael G. Kenward
address problems in this area. In “Semiparametric Estimation of
14 AMSTAT NEWS DECEMBER 2008
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